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Gradient-Based Low-Light Image Enhancement

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Masayuki Tanaka, Takashi Shibata, Masatoshi Okutomi

Computer Vision and Pattern Recognition · Submitted 25 Sep 2018

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Experiments demonstrate that the proposed gradient-based low-light image enhancement can effectively enhance the low-light images.

how it is stated · asserted 1.00 read the record →

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arXiv ID1809.09297 (version 1)
Pith IDTUVF7VU4, Pith's permanent record of this paper and its review
CitationMasatoshi Okutomi, Masayuki Tanaka, Takashi Shibata. "Gradient-Based Low-Light Image Enhancement." arXiv:1809.09297 (2018). https://pith.science/paper/TUVF7VU4
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 4,774 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.06 · human participants 0.04 · controlled comparison 0.06 · randomized assignment 0.01 · states quantitative result 0.04 · compares with prior results 0.06 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones. In this paper, a gradient-based low-light image enhancement algorithm is proposed. The key is to enhance the gradients of dark region, because the gradients are more sensitive for human visual system than absolute values. In addition, we involve the intensity-range constraints for the image integration. By using the intensity-range constraints, we can integrate the output image with enhanced gradients preserving the given gradient information while enforcing the intensity range of the output image within a certain intensity range. Experiments demonstrate that the proposed gradient-based low-light image enhancement can effectively enhance the low-light images.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones. background 1.00 0.04 0.02 asserted 1.00
s1 In this paper, a gradient-based low-light image enhancement algorithm is proposed. contribution 1.00 0.86 0.05 asserted 0.98
s2 The key is to enhance the gradients of dark region, because the gradients are more sensitive for human visual system than absolute values. method 0.80 0.23 0.07 asserted 1.00
s3 In addition, we involve the intensity-range constraints for the image integration. method 0.78 0.89 0.03 asserted 0.94
s4 By using the intensity-range constraints, we can integrate the output image with enhanced gradients preserving the given gradient information while enforcing the intensity range of the output image within a certain intensity range. method 0.99 0.83 0.08 asserted 0.85
s5 Experiments demonstrate that the proposed gradient-based low-light image enhancement can effectively enhance the low-light images. result 0.99 0.95 0.91 asserted 1.00

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from observation or experiment 0.99.

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  • references and citing sentences
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  • P abstract
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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones. In this paper, a gradient-based low-light image enhancement algorithm is proposed. The key is to enhance the gradients of dark region, because the gradients are more sensitive for human visual system than absolute values. In addition, we involve the intensity-range constraints for the image integration. By using the intensity-range constraints, we can integrate the output image with enhanced gradients preserving the given gradient information while enforcing the intensity range of the output image within a certain intensity range. Experiments demonstrate that the proposed gradient-based low-light image enhancement can effectively enhance the low-light images.

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